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Harvesting metaphors

[[some metaphors]]

[[data_tree_biology]]

[[sewage_forest_air]]

1st collection
What if we look at promiscuitiy as a natural state?
Promiscuous connections?
Different levels of symbiosis: physical, emotional, communicative
talking about herbarium/fungarium/xylarium/hortorium instead of manual for instance : what does that bring into imaginary of computer use ?
leafing (;-)) through the index/contents for the book "programming languages, history and fundamentals" by Jean E Sammet from 1969, no references (except bugs) to words related to nature were found, would it be that older programming languages were made by mathematici?ans, and that later on other lexicon than mathematics were used to describe digital process ?

2 different uses of metaphors:
use of metaphorical meaning, ex 'root'
inspiration on natural processes to design new systems: ex neural systems ... (see [[system notes]])

'Tree' goes back to Darwin, has shaped our knowledge; graphical use interface
relation to contemporary biotechnology concept, non-hierarchical

Vocabulary from morning meeting
* symbiosis
* ecology
* ecosystem
* Trees and Forests Trees
comes from :
    https://en.wikipedia.org/wiki/Active_Directory
    http://serverfault.com/questions/180980/what-is-meant-by-a-multi-forest-environment
* Rhizome
* osmosis

THINGS
* the mouse
* apple
* stream
* flow
* flux
* flooding

ALGORITHMS / PROGRAMMING
* tree structures (< Concepts, techniques and models for computer Programming, Peter Van Roy & co, p. 150)
finite tree, binary tree, ...  ---> L-system
* genetic algorithms & DNA-structures: https://en.wikipedia.org/wiki/Genetic_algorithm
* clone
* shell scripting
* cascading
* handling cycles
* bug / debugging: comes from a real bug! a moth !
* worm
* git merge octopus (also mentions of trees, branchs...) https://www.git-scm.com/docs/git-merge
* composite pattern (p.535)
* nesting
* flow control (261)
* atoms (824)
* pruning
* source (code)
* web
* hive
* root
* python
* animals as name of software (and subsequent versions), mascots...
* seeding / leeching

SYSTEMS
-------
% GRAFT: Systems, inventory
* evolutionary systems (fitness)
* neural network
* cellular systems (cellular automata)
* innmune systems (antivirus)
* ant colony 
* particle swarm

PROPERTIES OF ORGANIC SYSTEMS
-----------------------------
% GRAFT: Organic systems
_Structure_ aggregation of elements to form more complex structures
_Appearance_ visual expression of internal state
_Metabolism_ synthesis of nutrients for raw materials and fuel
_Growth_ an increase in either scale or amount of structure
_Homeostasis_ the maintenance of a balanced internal state
_Responsiveness_ reaction to stimuli and awareness of the environment
_Adaptation_ adjustments to survive in a changing environment
_Movement_ behavioral expression of internal state
_Reproduction_ the ability of entities to create others like itself

BOOKS
Insect Media - An Archaeology of Animals and Technology
http://www.upress.umn.edu/book-division/books/insect-media
../bibliotecha/Insect%20Media_%20An%20Archaeology%20of%20Animals%20and%20Technology%20-%20Jussi%20Parikka.pdf
http://www.igi-global.com/book/biologically-inspired-computing-arts/60763
http://docs.lib.purdue.edu/cgi/viewcontent.cgi?article=2448&context=cstech
../bibliotecha/2012_IGI.pdf
../bibliotecha/DeRosnay.TheSymbioticMan.pdf
../bibliotecha/mathematical%20models%20in%20biology.pdf
../bibliotecha/abop.pdf
../bibliotecha/ia_9780262062718.pdf
../bibliotecha/%5bPeter_Van_Roy,_Seif_Haridi%5d_Concepts,_Techniques.pdf

Gottfried's scraping of functions in Linux kernel:
% GRAFT: organic, vocabulary
 words found in the kernel that relate to nature (1st read, perhaps some were forgotten) :
 root, head, tail, leaf, trees, watchdog, bat, nested, flock, cows, poodle, canary
 not sure :
savage, tea, cork, storm, coffee, haystack
"In other words, if I were to model an contain messages geared towards users rather abstract piece of code based on my knowledge than internal concepts. Also discarded were of how an escalator works - I would likely comments in the code as its prose can only name it “escalator” (with a function “call”, be inadequately captured in a word list. for example)." [^]{../bibliotecha/source_contents_booklet.pdf]}

ARTISTS
Kuai Shen http://kuaishen.tv/
Martin Howse http://lib.fo.am/parn/radio_mycelium + http://www.1010.co.uk/org/sketches.html + http://www.1010.co.uk/
Angelo Vermuelen http://www.angelovermeulen.net/?portfolio=biomodd
Gilberto Esparza http://plantasnomadas.com/
Adam W. Brown and Robert Root-Bernstein http://prix2015.aec.at/prixwinner/15303/
Stephane Degoutin, Gwenola Wagon http://worldbrain.arte.tv/#/


Reading
Tree structures in 3. Programming with recursion
parse tree - sentence diagramming
binary trees iN Python: http://cbio.ufs.ac.za/live_docs/nbn_tut/trees.html
tree data model ../bibliotecha/ch05.pdf
Ternary tree for words: http://www.geeksforgeeks.org/ternary-search-tree/

a tree is a pipeline ?!?

decision-tree

-----

INTERVIEWS

Michael
orderable / 'total ordering'
has to be communicative - > makes assumptions of where things are
writing black/red tree, to replace videowiki code to write subtitles

interval trees: specific data structure to manage intervals, ith starting and ending point
scrubbing a video, wan tto know what subtitles / notes are there, you pull them up
very fast to have things added and removed from
ex lots of different sources (youtube comments/wikipedia entries), swithc them on & off
a normal tree would make a list
cost is associated with heigth of a tree
you can connect text/files to the nodes of numbers
ex. sorting your music collection alphabetically by title (name = key value / root = F)
--> a series of procedures to delete/add stuff, if you don't follow them, you risk to break it

protocol
play video & periodically check the time (ex 4x:second)
then you just see changes / overlaps (?)
normal subtitle file is sequential

AA-tree
self balancing tree, more simple

trees are very basic
structure as a response to your content
as a programmer you take what is given - generic stuff:
lists, associative arrays (generic, take any data)
computer have gone faster, so it doesn't really matter that it doesn't go fast

--------

Walt Whitman

LEAVES OF GRASS By Walt Whitman

For Him I Sing
  For him I sing,
  I raise the present on the past,
  (As some perennial tree out of its roots, the present on the past,)
  With time and space I him dilate and fuse the immortal laws,
  To make himself by them the law unto himself.
  

For later use:
THE LESSON OF A TREE - part of Specimen Days [1882]


Sept. 1.—I should not take either the biggest or the most picturesque tree to illustrate it. Here is one of my favorites now before me, a fine yellow poplar, quite straight, perhaps 90 feet high, and four thick at the butt. How strong, vital, enduring! how dumbly eloquent! What suggestions of imperturbability and being, as against the human trait of mere seeming. Then the qualities, almost emotional, palpably artistic, heroic, of a tree; so innocent and harmless, yet so savage. It is, yet says nothing. How it rebukes by its tough and equable serenity all weathers, this gusty-temper'd little whiffet, man, that runs indoors at a mite of rain or snow. Science (or rather half-way science) scoffs at reminiscence of dryad and hamadryad, and of trees speaking. But, if they don't, they do as well as most speaking, writing, poetry, sermons—or rather they do a great deal better. I should say indeed that those old dryad-reminiscences are quite as true as any, and profounder than most reminiscences we get. ("Cut this out," as the quack mediciners say, and keep by you.) Go and sit in a grove or woods, with one or more of those voiceless companions, and read the foregoing, and think.
% GRAFT: categories, inherency
One lesson from affiliating a tree—perhaps the greatest moral lesson anyhow from earth, rocks, animals, is that same lesson of inherency, of what is, without the least regard to what the looker-on (the critic) supposes or says, or whether he likes or dislikes. What worse—what more general malady pervades each and all of us, our literature, education, attitude toward each other, (even toward ourselves,) than a morbid trouble about seems, (generally temporarily seems too,) and no trouble at all, or hardly any, about the sane, slow-growing, perennial, real parts of character, books, friendship, marriage—humanity's invisible foundations and hold-together? (As the all-basis, the nerve, the great-sympathetic, the plenum within humanity, giving stamp to everything, is necessarily invisible.)[^]{Walt Whitman, The Lesson of a tree (1882)}

Aug. 4, 6 P.M.—Lights and shades and rare effects on tree-foliage and grass—transparent greens, grays, &c., all in sunset pomp and dazzle. The clear beams are now thrown in many new places, on the quilted, seam'd, bronze-drab, lower tree-trunks, shadow'd except at this hour—now flooding their young and old columnar ruggedness with strong light, unfolding to my sense new amazing features of silent, shaggy charm, the solid bark, the expression of harmless impassiveness, with many a bulge and gnarl unreck'd before. In the revealings of such light, such exceptional hour, such mood, one does not wonder at the old story fables, (indeed, why fables?) of people falling into love-sickness with trees, seiz'd extatic with the mystic realism of the resistless silent strength in them—strength, which after all is perhaps the last, completest, highest beauty.

% GRAFT: Organic systems
**Trees I am familiar with here.**    
%
   Oaks, (many kinds—one sturdy                       Willows.
     old fellow, vital, green, bushy,                  Catalpas.
     five feet thick at the butt, I sit                Persimmons.
     under every day,)                                 Mountain-ash.
   Cedars plenty.                                      Hickories.
   Tulip trees, (Liriodendron,) is of                Maples, many kinds.
     the magnolia family—I have                       Locusts.
     seen it in Michigan and southern                  Birches.
     Illinois, 140 feet high and                       Dogwood.
     8 feet thick at the butt {A}; does                Pine.
     not transplant well; best rais'd                  the Elm.
     from seeds—(the lumbermen                        Chesnut.
     call it yellow poplar.)                           Linden.
   Sycamores.                                          Aspen.
   Gum trees, both sweet and sour.                     Spruce.
   Beeches.                                            Hornbeam.
   Black-walnuts.                                      Laurel.
   Sassafras.                                          Holly.